Learning health systems need to bridge the 'two cultures' of clinical informatics and data science
Learning health systems need to bridge the 'two cultures' of clinical informatics and data science
Background UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational 'Big Data'. Learning health systems require not only data, but feedback loops of knowledge into changed practice. This depends on knowledge management and application, which in turn depends upon effective system design and implementation. Biomedical informatics is the interdisciplinary field at the intersection of health science, social science and information science and technology that spans this entire scope. Issues In the UK, the separate worlds of health data science (bioinformatics, 'Big Data') and effective healthcare system design and implementation (clinical informatics, 'Digital Health') have operated as 'two cultures'. Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on 'data cleansing' or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. Recommendation The UK needs increased clinical informatics research and education capacity and capability at much greater scale and ambition to be able to meet policy expectations, address the fundamental gaps in the discipline's evidence base and mitigate the absence of regulation. Independent evaluation of digital health interventions should be the norm, not the exception. Conclusions Policy makers and research funders need to acknowledge the existing gap between the 'two cultures' and recognise that the full social and economic benefits of digital health and data science can only be realised by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.
Big data, Bioinformatics, Education, Evidence-based practice, Health informatics, Health policy, Learning health systems, Programme evaluation
126-131
Scott, Philip J.
64f15a3f-7fe9-4ee3-b241-50d954ff5bd5
Dunscombe, Rachel
4afbf827-7dee-4147-955e-73cf4ce69a53
Evans, David
cb438f55-5980-4a29-959d-6e03a54eb112
Mukherjee, Mome
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Wyatt, Jeremy C.
8361be5a-fca9-4acf-b3d2-7ce04126f468
June 2018
Scott, Philip J.
64f15a3f-7fe9-4ee3-b241-50d954ff5bd5
Dunscombe, Rachel
4afbf827-7dee-4147-955e-73cf4ce69a53
Evans, David
cb438f55-5980-4a29-959d-6e03a54eb112
Mukherjee, Mome
b4383a34-269e-4d5d-a2f1-073dd8dd9766
Wyatt, Jeremy C.
8361be5a-fca9-4acf-b3d2-7ce04126f468
Scott, Philip J., Dunscombe, Rachel, Evans, David, Mukherjee, Mome and Wyatt, Jeremy C.
(2018)
Learning health systems need to bridge the 'two cultures' of clinical informatics and data science.
Journal of Innovation in Health Informatics, 25 (2), .
(doi:10.14236/jhi.v25i2.1062).
Abstract
Background UK health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational 'Big Data'. Learning health systems require not only data, but feedback loops of knowledge into changed practice. This depends on knowledge management and application, which in turn depends upon effective system design and implementation. Biomedical informatics is the interdisciplinary field at the intersection of health science, social science and information science and technology that spans this entire scope. Issues In the UK, the separate worlds of health data science (bioinformatics, 'Big Data') and effective healthcare system design and implementation (clinical informatics, 'Digital Health') have operated as 'two cultures'. Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on 'data cleansing' or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. Recommendation The UK needs increased clinical informatics research and education capacity and capability at much greater scale and ambition to be able to meet policy expectations, address the fundamental gaps in the discipline's evidence base and mitigate the absence of regulation. Independent evaluation of digital health interventions should be the norm, not the exception. Conclusions Policy makers and research funders need to acknowledge the existing gap between the 'two cultures' and recognise that the full social and economic benefits of digital health and data science can only be realised by accepting the interdisciplinary nature of biomedical informatics and supporting a significant expansion of clinical informatics capacity and capability.
Text
1062-3506-1-PB
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Accepted/In Press date: May 2018
e-pub ahead of print date: 15 June 2018
Published date: June 2018
Keywords:
Big data, Bioinformatics, Education, Evidence-based practice, Health informatics, Health policy, Learning health systems, Programme evaluation
Identifiers
Local EPrints ID: 424816
URI: http://eprints.soton.ac.uk/id/eprint/424816
ISSN: 2058-4555
PURE UUID: b13ca9c1-58aa-46ec-9b6a-d5be96cf1f4c
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Date deposited: 05 Oct 2018 11:48
Last modified: 16 Mar 2024 04:23
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Contributors
Author:
Philip J. Scott
Author:
Rachel Dunscombe
Author:
David Evans
Author:
Mome Mukherjee
Author:
Jeremy C. Wyatt
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